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Capturing contextual relationship for effective media search

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Abstract

One of the central problems regarding media search is the semantic gap between the low-level features computed automatically from media data and the human interpretation of them. This is because the notion of similarity is usually based on high-level abstraction but the low-level features do not sometimes reflect the human perception. In this paper, we assume the semantics of media is determined by the contextual relationship in a dataset, and introduce the method to capture the contextual information from a large media (especially image) dataset for effective search. Similarity search in an image database based on this contextual information shows encouraging experimental results.

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Authors and Affiliations

  1. Department of Computer Engineering, Seoul National University of Science and Technology, Seoul, 139-743, South Korea

    Guang-Ho Cha

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  1. Guang-Ho Cha
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Correspondence to Guang-Ho Cha.

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Cha, GH. Capturing contextual relationship for effective media search. Multimed Tools Appl 56, 351–364 (2012). https://doi.org/10.1007/s11042-010-0670-4

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  • DOI: https://doi.org/10.1007/s11042-010-0670-4

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